1. Field of the Invention
The present invention relates to a method of classifying defects. More particularly, the present invention relates to a method of rapidly inspecting and classifying defects such as particles or scratches on an object such as a semiconductor substrate.
2. Description of the Related Arts
A semiconductor fabricating process indispensably requires a process for inspecting detects on an object such as a semiconductor substrate. For example, after forming fine patterns on the semiconductor substrate using a photolithography process, defects such as particles, bridges, or collapses may be generated on these patterns. In addition, scratches may be generated on a surface on the semiconductor substrate after performing a chemical mechanical polishing (CMP) process.
According to a conventional method of inspecting defects, light having a specific wavelength is irradiated onto the object to detect defects. Often the defects are not accurately detected. Further, types of the detected defects are not automatically classified. These problems may be caused by large jumps in data values with respect to the defects in accordance with the diverse shapes of the defects, normal features, or properties of layers on the object. As a result, characteristic information that is to be used for recognizing the defects on the object and for distinguishing the types of the defects is lacking. Thus, the conventional method does not accurately detect defects on the object, and does not automatically classify the types of defects that are detected.
FIG. 1 is a flow chart illustrating a conventional method of classifying defects on an object.
Referring to FIG. 1, in step S10, a defect-inspecting apparatus irradiates light having a specific wavelength onto a surface of a wafer to scan its surface. In step S20, the defect inspecting apparatus obtains information concerning existence, numbers and coordinates of defects on the wafer. In step S30, a server then stores this information.
In step S40, it is determined whether the number of defects exceeds a predetermined allowable number. If so, then the semiconductor's fabricating equipment may be suspended. Subsequently, in step S50, the wafer is transferred to a review tool. The review tool performs a review process on the wafer. Here, the review process corresponds to a process for identifying the shapes and formations of the defects on the wafer by an inspector's eye using the review tool based on the information concerning the defects. Examples of the review tool include a microscope, a scanning electron microscope (SEM), etc.
The review process identifies the types of the defects that exceed the allowable numbers on the wafer and determines whether the defects affect the semiconductor manufacturing processes. In step S60, an inspector directly identifies the defects by the naked eye to determine whether the defects critically affect the semiconductor-manufacturing processes. When the defects on the wafer exceed the allowable numbers, in step S70, the following process is suspended. On the contrary, when the defects on the wafer do not exceed the allowable numbers, in step S80, the following process may begin.
FIGS. 2 and 3 are graphs illustrating a conventional method of classifying defects using a manually reviewing process.
Referring to FIG. 2, when the number of detected defects is beyond a predetermined reference number of about 200, for example, the wafer is reviewed while suspending the subsequent processes.
In the review process, a worker, i.e., the inspector, visually inspects the defects on the wafer. The worker manually classifies the types of the defects, and then inputs the information concerning the classified defects into a server. The types of stored defects are classified as shown in FIG. 3. For example, when defects of a type II correspond to a critical defect, the subsequent process is suspended in accordance with the number of the defects of type II.
In the conventional method, whether the review process is performed is determined in accordance with the number of the defects on the wafer. Thus, when the number of the detected defects is below the reference number and a critical defect is included among the detected defects, the conventional method may not recognize the defect. This case often occurs in semiconductor manufacturing processes. A reference number of the defects may be adjusted in the following processes. In fact, a reference number of the defects may frequently be changed during the course of a number of manufacturing processes.
When the number of defects is in the hundreds or thousands, the review process is too long so that all the defects are not actually classified. Thus, the inspector randomly selects some wafers and reviews the defects on the selected wafers. The inspector speculates on the number and a ratio of the defects by multiplying the reviewed defects by a constant multiple factor. However, since the selected wafer does not accurately represent all the wafers, the conventional method has poor reliability. Furthermore, since the conventional method is dependent upon the subjective judgment of the inspector, the classification of the defects by the manual reviewing process may often lack objectivity.
For example, the conventional inspecting apparatus inspects about 200 to about 300 wafers per day. About 1,400 to 2,100 wafers may be inspected per day in one semiconductor-fabricating line using seven inspecting apparatuses. A small number of wafers are actually reviewed among the inspected wafers. Particularly, since a small number of wafers having many defects are reviewed, defect inspection results have poor accuracy.
Furthermore, since the conventional method uses light having a single wavelength, the defects are not precisely detected. Particularly, the detected defects are not automatically classified.
FIG. 4 is a picture illustrating a first image obtained by irradiating red (610 to 700 nm) light onto a particle. FIG. 5 is a picture illustrating a second image obtained by irradiating green (450 to 500 nm) light onto the same particle. FIG. 6 is a picture illustrating a third image obtained by irradiating blue (400 to 450 nm) light onto the particle.
Referring to FIGS. 4 to 6, the first, second and third images P1, P2 and P3 are of the same particle. However, as shown in these figures, although the first, second and third defect images P1, P2 and P3 are of the same particle, the first, second and third images P1, P2 and P3 are quite different from each another.
The size of the third defect image P3 is smaller than that of the second defect image P2, and the size of the second defect image P2 is smaller than that of the first defect image P1. That is, the sizes of the defect images P1, P2 and P3 gradually decrease in accordance with their respective imaging wavelengths. Further, the shapes of the defect images P1, P2 and P3 are also different. Particularly, the first defect image P1 in FIG. 4 has a substantially circular shape. On the contrary, the second defect image P2 in FIG. 5 has a vertically long oval shape, and the third defect image P3 in FIG. 6 has a horizontally long rectangular shape. That is, a width, a height, an area, a slope, etc., of the defect images P1, P2 and P3 varies in accordance with their imaging wavelengths.
Furthermore, the brightness of the first defect image P1 in FIG. 4 and a brightness of the second defect image P2 in FIG. 5 gradually decrease from a peripheral portion of the images to a central portion of the images. However, the third defect image P3 in FIG. 5 does not have the above-mentioned brightness characteristics of the first and second images P1 and P2. Thus, existence of a defect on the third defect image P3 is not distinctly identified.
As described above, the data with respect to the defects varies in accordance with the wavelength of the light so that the defects are not accurately classified using light having a single wavelength. Further, the existence of the defects is not recognized using this light.
To overcome the above-mentioned problems caused by the light having a single wavelength, a method and an apparatus for classifying defects using various polarized light is disclosed in Korean Patent Laid-Open Publication No. 2004-76742. Further, a method and an apparatus for classifying defects using laser beams having different wavelengths are disclosed in Japan Laid-Open Publication No. 2002-116155. However, although above-mentioned Publications disclose techniques for readily detecting defects using various types of light, the Publications fail to disclose techniques for accurately classifying detected defects.
Because the semiconductor device is highly integrated, tens of defects may have typically been on a single substrate in the past, whereas, today, hundreds or thousands of defects are currently generated on the single substrate. However, a method of effectively classifying detected defects has not developed. Thus, a method of effectively classifying defects to increase the productivity of semiconductor device manufacturing is urgently in demand.